Microsoft Speech SDK Research Articles

Feasibility Study on Automatic Surgical Phase Identification based on Speech Recognition for Laparoscopic Prostatectomy.

An efficient capacity management of the Operation Room (OR) is crucial for the optimization of resources and consequent cost minimization. However, the duration of each surgery is hard to predict and often prone to variability and unforeseen events that may delay or accelerate each procedure. Automatic surgical phase identification strategies can lead to a more accurate and automated estimation of the surgery duration, improving OR schedule optimization. One possible contribution for these methods is the introduction of speech recognition systems. The described work aims at the implementation of a speech recognition (SR) engine for surgical phase identification, specifically optimized for Laparoscopic Radical Prostatectomy (LRP). For this application the performance of 3 engines was tested under different background noise and distance circumstances: Microsoft Speech SDK; Google Speech Recognition API; and an optimization of the first, with the introduction of specific vocabulary. Action/target binomials were used to identify the Laparoscopic Prostatectomy surgical phases. 15 participants were selected to perform the tests and Word Error Rate (WER) was calculated as the main comparison metric. The values for the total WER indicate that AzureGrammar (specific vocabulary inserted) has superior performance, reaching a lower error rate of 29.25%, when compared to Azure and Google with 67.91% and 67.48%, respectively. Phase Accuracy Ratio (PAR), considering only the AzureGrammar SR engine, are 84% and 83%, for 1 m and 2 m, without background noise; 61% and 51%, for 1 m and 2 m, with background noise. This study demonstrates that using a conventional SR engine, with specific vocabulary incorporated, has the potential to achieve an acceptable performance with minimal setup. Clinical Relevance- Speech based, surgical phase identification, can be achieved with minimal setup to existing SR engines, showing potential to be implemented in Operating Room, with further optimization.

Speech recognition in flight simulator

The article is devoted to the investigation of speech recognition in Flight Simulator cockpit. We have done research and developed software for speech recognition in Flight Simulator with limited vocabulary in C# from scratch. The speech recognition system works in real time and offline mode in Windows platform. We used Mel Frequency Cepstral Coefficients and Linear Predictive Coefficients feature extraction algorithms and trained the system by multilayer artificial neural networks. The User Interface of platform is highly functional and allows users to update system parameters through the interface. Our Speech Recognition system results are compared to the results of Microsoft Speech SDK and received satisfactory achievement.

Research on multimodal human-robot interaction based on speech and gesture

This paper presents a multimodal human-robot interaction based on fusion of speech and gesture. In the interface, a robot control command system is designed, which can transform the speech and gesture of users into commands that the robot can execute. Microsoft speech SDK is used in this system to collect the speech of the operator. Then, a corpus-based algorithm of maximum entropy classification for natural language understanding is employed to generate commands. Leap Motion is employed to capture the gesture of operator in this system. Interval Kalman Filter (IKF) is used to estimate the measured data to reduce the inherent noise of the sensor. The advantage of the proposed method is that the combination of speech and gesture makes the human-robot interaction more convenient and direct. Finally, a series of experiments were carried out to validate our method, and proved that it performed better than the other proposed methods.

The Application of Multimedia Grid in Barrier-Free for Special Education

A speech navigation teaching assistant system for multimedia grid is designed based on the multimedia grid technology, the TTS technology and Microsoft speech SDK. The multimedia grid technology are introduced firstly, then the system application platform, the structure of resource management and functions are detailed described, lastly the key technology and implement way is given. This system for the application areas of special education for information barrier-free have certain guiding significance and the actual practical application value.

The Service Platform for Barrier-Free Special Education Based on Cloud Computing

Cloud computing is a computing model, computing and storage tasks be assigned to the cloud that be composed of a large number of computers. The cloud computing technology are introduced firstly, then the cloud network platform, the service platform for barrier-free special education and functions are detailed described, lastly the key technology is given, such as TTS technology, Microsoft Speech SDK.

Design and Implementation of Voice Control System in Flexible Manufacturing Cell

On the voice development platform of Microsoft Speech SDK, speech recognition and speech synthesis modules based on command control mode is built in this paper. Ethernet-based remote voice control system of intelligent flexible manufacturing cell is developed for machine tools and industrial robots. This paper designs an intelligent voice control system based on LabVIEW development environment, which realizes the human-machine voice interaction of flexible manufacturing cell and remote voice control. Experimental studies have shown that intelligent voice control system has high speech recognition rate and system reliability in a relatively quiet environment.

An intelligent multimedia interface for fuzzy-logic based inference in crops

The paper reports an interface designed for three subsystems—the knowledge acquisition subsystem with dynamic disease knowledge base, intelligent disease diagnosis subsystem with object-oriented intelligent-inference model and intelligent tutor for crop disease with audio-visual graphical user web-interface. The paper describes the design features; functionality and development of intelligent multimedia web interface. The results of its evaluation are also presented. A novel approach of rule promotion based on fuzzy logic is used in the system for drawing intelligent inferences for crop disease management. A text-to-speech (TTS) converter is used for providing capability of text-to-talking user interface. It provides the highly-effective interactive user interface on web for live interactions. It helps significantly and gives solutions of plant pathological problems in short spell. The application software is built using the Microsoft .NET framework, ASP.NET web-application framework provided in Visual Studio.NET. The Microsoft Speech SDK (5.1) is used to develop text to voice multimedia interface. The dynamic knowledge base is implemented using SQL server.

Developing a Wireless Speech- and Touch-Based Intelligent Comprehensive Triage Support System

The implementation of voice recognition technology has been expected to occur in mobile healthcare settings, but it is the least studied solution in nursing. The objective of this study is to examine its value to mobile nursing. The study was done at a triage station in an emergency department. The system was developed using VB6.0, Microsoft Speech SDK 5.1 and the Simplified Chinese Language pack, and was installed on touchscreen PCs with wireless headsets. Thirty nurses were enrolled. Accuracy rate and operation time were used to measure the subjects' performance. A "willingness to use" score on a scale of 1 to 10 was used to measure subjects' preference for the system. The results showed that the average accuracy rate was 99%, the average operation time was 108 seconds, and the mean "willingness to use" rating was 8.2. This study demonstrates the value of multimodal voice recognition techniques to mobile nursing.

Robot‐by‐voice: experiments on commanding an industrial robot using the human voice

PurposeThis paper reports a few results of an ongoing research project that aims to explore ways to command an industrial robot using the human voice. This feature can be interesting with several industrial, laboratory and clean‐room applications, where a close cooperation between robots and humans is desirable.Design/methodology/approachA demonstration is presented using two industrial robots and a personal computer (PC) equipped with a sound board and a headset microphone. The demonstration was coded using the Microsoft Visual Basic and C#.NET 2003 and associated with two simple robot applications: one capable of picking‐and‐placing objects and going to predefined positions, and the other capable of performing a simple linear weld on a work‐piece. The speech recognition grammar is specified using the grammar builder from the Microsoft Speech SDK 5.1. The paper also introduces the concepts of text‐to‐speech translation and voice recognition, and shows how these features can be used with applications built using the Microsoft.NET framework.FindingsTwo simple examples designed to operate with a state‐of‐the‐art industrial robot manipulator are then built to demonstrate the applicability to laboratory and industrial applications. The paper is very detailed in showing implementation aspects enabling the reader to explore immediately from the presented concepts and tools. Namely, the connection between the PC and the robot is explained in detail since it was built using a RPC socket mechanism completely developed from the scratch.Practical implicationsFinally, the paper discusses application to industrial cases where close cooperation between humans and robots is necessary.Originality/valueThe presented code and examples, along with the fairly interesting and reliable results, indicate clearly that the technology is suitable for industrial utilization.